How a single
agent (human, firm, animal, etc.) behaves typically depends on what
information it has about its environment, and on its preferences.
Accordingly, the joint behavior of multiple interacting agents can
depend strongly on the information available to the separate agents,
both about one another, and about external random variables. Precisely
how the joint behavior depends on the information available to the
agents is determined by the preferences of those agents. So in general
there is a strong interplay among the preferences of all the agents,
their behavior, and the information structure connecting them.

One
tool that might help us understand this interplay is Shannon
information theory. In Shannon information theory, information is a
function of a distribution. Increasing the amount of information in a
distribution means making that distribution more tightly concentrated.
This definition applies not only if the support of the distribution
shrinks or expands, but also if it moves.

Another tool that might
help us understand the interplay is game theory. In contrast to Shannon
information theory, game theory does not quantify information in terms
of properties of probability distributions. Rather the information
available to a player is quantified as an "information set," specifying
a set of states the world might be in. The amount of information
available to a player increases if such an information set shrinks. In
contrast to the case with Shannon information theory, the change in
information for moving an information set is undefined.

There
are other differences between information theory and game theory. For
example, whereas the foundations of Shannon information theory concern a
single player (the designer of a communication network), the
foundations of game theory concern multiple players.

Reconciling
the different perspectives on information in Shannon information theory
and game theory could have many benefits. Most directly, it may help
us understand the interplay among the preferences of a set of
interacting players, their behavior, and the information structure
connecting them. As potential examples, it might help us address issues
like the following:

1. How do information theoretic
quantifications of the joint behavior of a set of interacting players
(e.g., mutual information between actions of pairs of them) vary with
changes to the preferences of those players?

2. Can relating the
philosophical foundations of the two fields improve them? For example,
as Shannon himself emphasized, Shannon information is purely
"syntactic," quantifying the amount of information in a distribution
purely by how concentrated it is. Can the utility functions of game
theory—which depend not just on how concentrated a distribution is, but
also on where it is concentrated—be used to define a "semantic" variant
of Shannon information?

3. Can relating the mathematical
formalisms of the two fields improve them? For example, are there
analogs of the powerful theorems of information theory for
game-theoretic quantities, e.g., game theoretic versions of results
concerning rate distortion tradeoffs, the data processing inequality,
etc.?

More generally, greater understanding of the relation
between information theory and game theory may generate breakthroughs in
many disciplines, including economics, political science, cognitive
sciences and artificial intelligence.

Aug. 7, 2013

Summary: Technological change is a key component of economic growth. However, economists' treatment of this is typically at an aggregate level, in which technology is represented merely as a single number called the "total factor productivity". This workshop will bring together researchers from a variety of disciplines to make first steps toward constructing a theory of technological change. The discussions will focus on understanding ecosystems of interacting technologies and the factors that cause them to evolve through time. Please join this foremost group of experts, economists, biologists, applied mathematicians, physicists, engineers, archaeologists, and anthropologists for a one-day event in Santa Fe.

The workshop is supported by the Santa Fe Institute, the Institute for New Economic Thinking and the U.S. Department of Energy.

Purpose: Business Network

Sept. 30, 2013

Summary: Business enterprises in general, and the modern corporation in particular, have become increasingly important elements in modern life and society. This topical meeting will address the historical origins of the modern corporation, the evolutionary nature of the firm, the impact of increasing globalization, the life cycle of the modern corporation, the implications of the "corporations are persons" doctrine in US law, and the relationship between corporations and other major social institutions such as cities.

Jan. 9, 2015

The past five+ years have been clouded by massive economic upheavals – and not just from the recession. The purpose of this Summit is to identify and resolve the issues that confront simulation software and the simulation software industry as we move beyond the recent economic crash and face new and complex challenges. We’re defining the simulation software industry as the ecosystem that creates or uses software to analyze, and simulate complex systems/products.

The need for simulation tools, products, and services has never been higher, yet we face major challenges limiting our ability to capitalize on that need. Some of those challenges are obvious to all, some less so – and there are more that we haven’t even considered yet. Attending the Summit will be a “who's who” of the CAE and engineering software industry: 40 visionaries, each with the role and position that empowers them to implement their vision.

A limited number of seats are available to Business Network Members. Please contact Casey Cox at casey@santafe.edu if you are interested in attending.